AI-Driven Privacy Security Engineer

Meta; Menlo Park (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Meta in Menlo Park seeks Security Engineers with privacy and data protection expertise to join our Applied AI organization. You will apply deep privacy engineering to hard, real-world problems in how data is collected, used, retained, exposed, and deleted.

Your work is AI-augmented from day one, leveraging AI tools to accelerate impact and improve model privacy. This role focuses on privacy at scale, production systems, and collaboration across teams to implement obligations tied to

Qualifications

• 8+ years of hands-on engineering experience in technical privacy, data protection, or privacy-adjacent security engineering.
• Deep expertise in at least one privacy subdomain with demonstrated ability to advance the state of the art: purpose limitation, retention and deletion, data access control, jurisdictional obligations, de-identification, consent, or ML and model privacy.

Responsibilities

• Design privacy systems and controls at scale across production environments.
• Collaborate with Applied AI and data teams to ensure privacy obligations are implemented in real-world data workflows.
• Lead efforts on de-identification, consent, data retention, deletion cascades, and jurisdictional requirements.

Skills

Privacy engineering

Production privacy implementation

Python/Java/C/C++

AI tools integration

Ethical AI practices

Data protection

Problem solving at scale

Model privacy

De-identification techniques

Education

BS/MS in CS or Cybersecurity

Job description

Meta in Menlo Park seeks Security Engineers with privacy and data protection expertise to join our Applied AI organization. You will apply deep privacy engineering to hard, real-world problems in how data is collected, used, retained, exposed, and deleted.

Your work is AI-augmented from day one, leveraging AI tools to accelerate impact and improve model privacy. This role focuses on privacy at scale, production systems, and collaboration across teams to implement obligations tied to